Predicting Software Development Project Outcomes

Case-based reasoning is a flexible methodology to manage software development related tasks. However, when the reasoner's task is prediction, there are a number of different CBR techniques that could be chosen to address the characteristics of a dataset. We examine several of these techniques to assess their accuracy in predicting software development project outcomes (i.e., whether the project is a success or failure) and identify critical success factors within our data. We collected the data from software developers who answered a questionnaire targeting a software development project they had recently worked on. The questionnaire addresses both technical and managerial features of software development projects. The results of these evaluations are compared with results from logistic regression analysis, which serves as a comparative baseline. The research in this paper can guide design decisions in future CBR implementations to predict the outcome of projects described with managerial factors.

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